Independent Security Researcher
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Yuvraj Pradhan is a security researcher working on agentic AI, where he breaks the trust boundaries production agent stacks depend on. His work covers LLM red teaming, MCP security, and approval-provenance failures in the persistence and resume paths shared by agent frameworks, workflow engines, and CI/CD systems, along with research into running offensive security workloads on small local models instead of frontier infrastructure. He is first author of Springer Nature research on a 125M-parameter language model for STEM tasks, and has spoken at MCP Dev Summit Bengaluru and Mumbai, both Linux Foundation events, with the Bengaluru session featured in the Agentic AI Foundation's official recap.
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